Knowledge graphs are well-suited for handling complex, multi-part questions because they store data as a network of nodes and the relationship between them. This connected data structure allows RAG apps to navigate from one piece of information to another efficiently, accessing all related information. The technique of combining RAG with knowledge graphs is known as GraphRAG. Building a RAG app with a knowledge graph improves query efficiency, especially when you’re dealing with connected data, and you can dump any type of data (structured and unstructured) into the graph without having to re-design the schema.